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A Nomogram for Predicting Mild Cognitive Impairment in Older Adults with Hypertension
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Abstract
Background: Hyper- and hypotension increase the risk of cognitive dysfunction. As effective control of blood pressure can reduce the risk of mild cognitive impairment(MCI), early risk assessment is necessary to identify mild cognitive impairment in senile hypertension as soon as possible and reduce the risk of developing dementia.
Method: This artical aims to explore the risk factors for MCI in older patients with hypertension and develop a nomogram model for predicting MCI. A total of 345 older patients with hypertension in Xixiangtang District, Nanning City were selected as modeling group(MG), and divided into MCI group (n=197) and non-MCI group(n=148). Comparing the general conditions, lifestyle, disease factors, psychosocial and other indicators of the two groups. Logistic regression was used to analyze risk factors for mild cognitive impairment in older hypertensive patients, and R Programming Language was used to draw the nomogram. A total of 146 older patients with hypertension in Qingxiu District, Nanning city were selected as verification group(VG). The effectiveness and discrimination ability of the nomogram were evaluated through internal and external verification.
Results: Multivariate logistic regression analysis identified 11 factors, including hypertension grade, education level, complicated diabetes, hypertension years, stress history, smoking, physical exercise, reading, social support, sleep disorders, and medication compliance, as risk factors for mild cognitive impairment in older community-dwelling patients with hypertension. To develop a nomogram model, the validity of the prediction model was evaluated by fitting the curve, which revealed a good fit for both the modeling (P = 0.98) and verification groups (P = 0.96). The discrimination of the nomogram model was evaluated in the modeling group using a receiver operating characteristic curve. The area under the curve was 0.795, sensitivity was 0.584, specificity was 0.919, Jordan Index was 0.503, positive-predictive value was 90.53%, negative-predictive value was 62.5%, and the Hosmer–Lemeshow test yielded P = 0.703. In the validation group, the area under the curve was 0.765, sensitivity was 0.63, specificity was 0.877, Jordan Index was 0.507, positive-predictive value was 84.46%, negative-predictive value was 65.52%, and the Hosmer–Lemeshow test yielded P = 0.234.
Conclusions: We developed a nomogram to help clinicians identify high-risk groups for mild cognitive impairment among community-dwelling older patients with hypertension. This model demonstrated good discrimination and validity, providing a scientific basis for community medical staff to evaluate and identify the risk of mild cognitive impairment in these patients at an early stage.
Title: A Nomogram for Predicting Mild Cognitive Impairment in Older Adults with Hypertension
Description:
Abstract
Background: Hyper- and hypotension increase the risk of cognitive dysfunction.
As effective control of blood pressure can reduce the risk of mild cognitive impairment(MCI), early risk assessment is necessary to identify mild cognitive impairment in senile hypertension as soon as possible and reduce the risk of developing dementia.
Method: This artical aims to explore the risk factors for MCI in older patients with hypertension and develop a nomogram model for predicting MCI.
A total of 345 older patients with hypertension in Xixiangtang District, Nanning City were selected as modeling group(MG), and divided into MCI group (n=197) and non-MCI group(n=148).
Comparing the general conditions, lifestyle, disease factors, psychosocial and other indicators of the two groups.
Logistic regression was used to analyze risk factors for mild cognitive impairment in older hypertensive patients, and R Programming Language was used to draw the nomogram.
A total of 146 older patients with hypertension in Qingxiu District, Nanning city were selected as verification group(VG).
The effectiveness and discrimination ability of the nomogram were evaluated through internal and external verification.
Results: Multivariate logistic regression analysis identified 11 factors, including hypertension grade, education level, complicated diabetes, hypertension years, stress history, smoking, physical exercise, reading, social support, sleep disorders, and medication compliance, as risk factors for mild cognitive impairment in older community-dwelling patients with hypertension.
To develop a nomogram model, the validity of the prediction model was evaluated by fitting the curve, which revealed a good fit for both the modeling (P = 0.
98) and verification groups (P = 0.
96).
The discrimination of the nomogram model was evaluated in the modeling group using a receiver operating characteristic curve.
The area under the curve was 0.
795, sensitivity was 0.
584, specificity was 0.
919, Jordan Index was 0.
503, positive-predictive value was 90.
53%, negative-predictive value was 62.
5%, and the Hosmer–Lemeshow test yielded P = 0.
703.
In the validation group, the area under the curve was 0.
765, sensitivity was 0.
63, specificity was 0.
877, Jordan Index was 0.
507, positive-predictive value was 84.
46%, negative-predictive value was 65.
52%, and the Hosmer–Lemeshow test yielded P = 0.
234.
Conclusions: We developed a nomogram to help clinicians identify high-risk groups for mild cognitive impairment among community-dwelling older patients with hypertension.
This model demonstrated good discrimination and validity, providing a scientific basis for community medical staff to evaluate and identify the risk of mild cognitive impairment in these patients at an early stage.
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